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Author

*The author of this computation has been verified*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Sat, 10 Dec 2011 04:27:20 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/10/t1323509253mky8qrv5k6hyupg.htm/, Retrieved Sat, 04 May 2024 21:50:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153454, Retrieved Sat, 04 May 2024 21:50:29 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

142

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Histogram] [ ] [2011-12-10 09:27:20] [87b6e955a128bfb8d1e350b3ce0d281e] [Current]

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Dataseries X:

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Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153454&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153454&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153454&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[0,5000[	2500	12	0.073171	0.073171	1.5e-05
[5000,10000[	7500	4	0.02439	0.097561	5e-06
[10000,15000[	12500	1	0.006098	0.103659	1e-06
[15000,20000[	17500	1	0.006098	0.109756	1e-06
[20000,25000[	22500	2	0.012195	0.121951	2e-06
[25000,30000[	27500	1	0.006098	0.128049	1e-06
[30000,35000[	32500	4	0.02439	0.152439	5e-06
[35000,40000[	37500	3	0.018293	0.170732	4e-06
[40000,45000[	42500	4	0.02439	0.195122	5e-06
[45000,50000[	47500	3	0.018293	0.213415	4e-06
[50000,55000[	52500	1	0.006098	0.219512	1e-06
[55000,60000[	57500	6	0.036585	0.256098	7e-06
[60000,65000[	62500	8	0.04878	0.304878	1e-05
[65000,70000[	67500	5	0.030488	0.335366	6e-06
[70000,75000[	72500	5	0.030488	0.365854	6e-06
[75000,80000[	77500	8	0.04878	0.414634	1e-05
[80000,85000[	82500	6	0.036585	0.45122	7e-06
[85000,90000[	87500	5	0.030488	0.481707	6e-06
[90000,95000[	92500	11	0.067073	0.54878	1.3e-05
[95000,1e+05[	97500	11	0.067073	0.615854	1.3e-05
[1e+05,105000[	102500	5	0.030488	0.646341	6e-06
[105000,110000[	107500	12	0.073171	0.719512	1.5e-05
[110000,115000[	112500	7	0.042683	0.762195	9e-06
[115000,120000[	117500	3	0.018293	0.780488	4e-06
[120000,125000[	122500	3	0.018293	0.79878	4e-06
[125000,130000[	127500	4	0.02439	0.823171	5e-06
[130000,135000[	132500	3	0.018293	0.841463	4e-06
[135000,140000[	137500	8	0.04878	0.890244	1e-05
[140000,145000[	142500	5	0.030488	0.920732	6e-06
[145000,150000[	147500	1	0.006098	0.926829	1e-06
[150000,155000[	152500	3	0.018293	0.945122	4e-06
[155000,160000[	157500	1	0.006098	0.95122	1e-06
[160000,165000[	162500	2	0.012195	0.963415	2e-06
[165000,170000[	167500	0	0	0.963415	0
[170000,175000[	172500	1	0.006098	0.969512	1e-06
[175000,180000[	177500	2	0.012195	0.981707	2e-06
[180000,185000[	182500	0	0	0.981707	0
[185000,190000[	187500	0	0	0.981707	0
[190000,195000[	192500	0	0	0.981707	0
[195000,2e+05[	197500	1	0.006098	0.987805	1e-06
[2e+05,205000[	202500	0	0	0.987805	0
[205000,210000[	207500	0	0	0.987805	0
[210000,215000[	212500	0	0	0.987805	0
[215000,220000[	217500	0	0	0.987805	0
[220000,225000[	222500	0	0	0.987805	0
[225000,230000[	227500	0	0	0.987805	0
[230000,235000[	232500	1	0.006098	0.993902	1e-06
[235000,240000]	237500	1	0.006098	1	1e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,5000[ & 2500 & 12 & 0.073171 & 0.073171 & 1.5e-05 \tabularnewline
[5000,10000[ & 7500 & 4 & 0.02439 & 0.097561 & 5e-06 \tabularnewline
[10000,15000[ & 12500 & 1 & 0.006098 & 0.103659 & 1e-06 \tabularnewline
[15000,20000[ & 17500 & 1 & 0.006098 & 0.109756 & 1e-06 \tabularnewline
[20000,25000[ & 22500 & 2 & 0.012195 & 0.121951 & 2e-06 \tabularnewline
[25000,30000[ & 27500 & 1 & 0.006098 & 0.128049 & 1e-06 \tabularnewline
[30000,35000[ & 32500 & 4 & 0.02439 & 0.152439 & 5e-06 \tabularnewline
[35000,40000[ & 37500 & 3 & 0.018293 & 0.170732 & 4e-06 \tabularnewline
[40000,45000[ & 42500 & 4 & 0.02439 & 0.195122 & 5e-06 \tabularnewline
[45000,50000[ & 47500 & 3 & 0.018293 & 0.213415 & 4e-06 \tabularnewline
[50000,55000[ & 52500 & 1 & 0.006098 & 0.219512 & 1e-06 \tabularnewline
[55000,60000[ & 57500 & 6 & 0.036585 & 0.256098 & 7e-06 \tabularnewline
[60000,65000[ & 62500 & 8 & 0.04878 & 0.304878 & 1e-05 \tabularnewline
[65000,70000[ & 67500 & 5 & 0.030488 & 0.335366 & 6e-06 \tabularnewline
[70000,75000[ & 72500 & 5 & 0.030488 & 0.365854 & 6e-06 \tabularnewline
[75000,80000[ & 77500 & 8 & 0.04878 & 0.414634 & 1e-05 \tabularnewline
[80000,85000[ & 82500 & 6 & 0.036585 & 0.45122 & 7e-06 \tabularnewline
[85000,90000[ & 87500 & 5 & 0.030488 & 0.481707 & 6e-06 \tabularnewline
[90000,95000[ & 92500 & 11 & 0.067073 & 0.54878 & 1.3e-05 \tabularnewline
[95000,1e+05[ & 97500 & 11 & 0.067073 & 0.615854 & 1.3e-05 \tabularnewline
[1e+05,105000[ & 102500 & 5 & 0.030488 & 0.646341 & 6e-06 \tabularnewline
[105000,110000[ & 107500 & 12 & 0.073171 & 0.719512 & 1.5e-05 \tabularnewline
[110000,115000[ & 112500 & 7 & 0.042683 & 0.762195 & 9e-06 \tabularnewline
[115000,120000[ & 117500 & 3 & 0.018293 & 0.780488 & 4e-06 \tabularnewline
[120000,125000[ & 122500 & 3 & 0.018293 & 0.79878 & 4e-06 \tabularnewline
[125000,130000[ & 127500 & 4 & 0.02439 & 0.823171 & 5e-06 \tabularnewline
[130000,135000[ & 132500 & 3 & 0.018293 & 0.841463 & 4e-06 \tabularnewline
[135000,140000[ & 137500 & 8 & 0.04878 & 0.890244 & 1e-05 \tabularnewline
[140000,145000[ & 142500 & 5 & 0.030488 & 0.920732 & 6e-06 \tabularnewline
[145000,150000[ & 147500 & 1 & 0.006098 & 0.926829 & 1e-06 \tabularnewline
[150000,155000[ & 152500 & 3 & 0.018293 & 0.945122 & 4e-06 \tabularnewline
[155000,160000[ & 157500 & 1 & 0.006098 & 0.95122 & 1e-06 \tabularnewline
[160000,165000[ & 162500 & 2 & 0.012195 & 0.963415 & 2e-06 \tabularnewline
[165000,170000[ & 167500 & 0 & 0 & 0.963415 & 0 \tabularnewline
[170000,175000[ & 172500 & 1 & 0.006098 & 0.969512 & 1e-06 \tabularnewline
[175000,180000[ & 177500 & 2 & 0.012195 & 0.981707 & 2e-06 \tabularnewline
[180000,185000[ & 182500 & 0 & 0 & 0.981707 & 0 \tabularnewline
[185000,190000[ & 187500 & 0 & 0 & 0.981707 & 0 \tabularnewline
[190000,195000[ & 192500 & 0 & 0 & 0.981707 & 0 \tabularnewline
[195000,2e+05[ & 197500 & 1 & 0.006098 & 0.987805 & 1e-06 \tabularnewline
[2e+05,205000[ & 202500 & 0 & 0 & 0.987805 & 0 \tabularnewline
[205000,210000[ & 207500 & 0 & 0 & 0.987805 & 0 \tabularnewline
[210000,215000[ & 212500 & 0 & 0 & 0.987805 & 0 \tabularnewline
[215000,220000[ & 217500 & 0 & 0 & 0.987805 & 0 \tabularnewline
[220000,225000[ & 222500 & 0 & 0 & 0.987805 & 0 \tabularnewline
[225000,230000[ & 227500 & 0 & 0 & 0.987805 & 0 \tabularnewline
[230000,235000[ & 232500 & 1 & 0.006098 & 0.993902 & 1e-06 \tabularnewline
[235000,240000] & 237500 & 1 & 0.006098 & 1 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153454&T=1

[TABLE]
[ROW][C]Frequency Table (Histogram)[/C][/ROW]
[ROW][C]Bins[/C][C]Midpoint[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][C]Cumul. Rel. Freq.[/C][C]Density[/C][/ROW]
[ROW][C][0,5000[[/C][C]2500[/C][C]12[/C][C]0.073171[/C][C]0.073171[/C][C]1.5e-05[/C][/ROW]
[ROW][C][5000,10000[[/C][C]7500[/C][C]4[/C][C]0.02439[/C][C]0.097561[/C][C]5e-06[/C][/ROW]
[ROW][C][10000,15000[[/C][C]12500[/C][C]1[/C][C]0.006098[/C][C]0.103659[/C][C]1e-06[/C][/ROW]
[ROW][C][15000,20000[[/C][C]17500[/C][C]1[/C][C]0.006098[/C][C]0.109756[/C][C]1e-06[/C][/ROW]
[ROW][C][20000,25000[[/C][C]22500[/C][C]2[/C][C]0.012195[/C][C]0.121951[/C][C]2e-06[/C][/ROW]
[ROW][C][25000,30000[[/C][C]27500[/C][C]1[/C][C]0.006098[/C][C]0.128049[/C][C]1e-06[/C][/ROW]
[ROW][C][30000,35000[[/C][C]32500[/C][C]4[/C][C]0.02439[/C][C]0.152439[/C][C]5e-06[/C][/ROW]
[ROW][C][35000,40000[[/C][C]37500[/C][C]3[/C][C]0.018293[/C][C]0.170732[/C][C]4e-06[/C][/ROW]
[ROW][C][40000,45000[[/C][C]42500[/C][C]4[/C][C]0.02439[/C][C]0.195122[/C][C]5e-06[/C][/ROW]
[ROW][C][45000,50000[[/C][C]47500[/C][C]3[/C][C]0.018293[/C][C]0.213415[/C][C]4e-06[/C][/ROW]
[ROW][C][50000,55000[[/C][C]52500[/C][C]1[/C][C]0.006098[/C][C]0.219512[/C][C]1e-06[/C][/ROW]
[ROW][C][55000,60000[[/C][C]57500[/C][C]6[/C][C]0.036585[/C][C]0.256098[/C][C]7e-06[/C][/ROW]
[ROW][C][60000,65000[[/C][C]62500[/C][C]8[/C][C]0.04878[/C][C]0.304878[/C][C]1e-05[/C][/ROW]
[ROW][C][65000,70000[[/C][C]67500[/C][C]5[/C][C]0.030488[/C][C]0.335366[/C][C]6e-06[/C][/ROW]
[ROW][C][70000,75000[[/C][C]72500[/C][C]5[/C][C]0.030488[/C][C]0.365854[/C][C]6e-06[/C][/ROW]
[ROW][C][75000,80000[[/C][C]77500[/C][C]8[/C][C]0.04878[/C][C]0.414634[/C][C]1e-05[/C][/ROW]
[ROW][C][80000,85000[[/C][C]82500[/C][C]6[/C][C]0.036585[/C][C]0.45122[/C][C]7e-06[/C][/ROW]
[ROW][C][85000,90000[[/C][C]87500[/C][C]5[/C][C]0.030488[/C][C]0.481707[/C][C]6e-06[/C][/ROW]
[ROW][C][90000,95000[[/C][C]92500[/C][C]11[/C][C]0.067073[/C][C]0.54878[/C][C]1.3e-05[/C][/ROW]
[ROW][C][95000,1e+05[[/C][C]97500[/C][C]11[/C][C]0.067073[/C][C]0.615854[/C][C]1.3e-05[/C][/ROW]
[ROW][C][1e+05,105000[[/C][C]102500[/C][C]5[/C][C]0.030488[/C][C]0.646341[/C][C]6e-06[/C][/ROW]
[ROW][C][105000,110000[[/C][C]107500[/C][C]12[/C][C]0.073171[/C][C]0.719512[/C][C]1.5e-05[/C][/ROW]
[ROW][C][110000,115000[[/C][C]112500[/C][C]7[/C][C]0.042683[/C][C]0.762195[/C][C]9e-06[/C][/ROW]
[ROW][C][115000,120000[[/C][C]117500[/C][C]3[/C][C]0.018293[/C][C]0.780488[/C][C]4e-06[/C][/ROW]
[ROW][C][120000,125000[[/C][C]122500[/C][C]3[/C][C]0.018293[/C][C]0.79878[/C][C]4e-06[/C][/ROW]
[ROW][C][125000,130000[[/C][C]127500[/C][C]4[/C][C]0.02439[/C][C]0.823171[/C][C]5e-06[/C][/ROW]
[ROW][C][130000,135000[[/C][C]132500[/C][C]3[/C][C]0.018293[/C][C]0.841463[/C][C]4e-06[/C][/ROW]
[ROW][C][135000,140000[[/C][C]137500[/C][C]8[/C][C]0.04878[/C][C]0.890244[/C][C]1e-05[/C][/ROW]
[ROW][C][140000,145000[[/C][C]142500[/C][C]5[/C][C]0.030488[/C][C]0.920732[/C][C]6e-06[/C][/ROW]
[ROW][C][145000,150000[[/C][C]147500[/C][C]1[/C][C]0.006098[/C][C]0.926829[/C][C]1e-06[/C][/ROW]
[ROW][C][150000,155000[[/C][C]152500[/C][C]3[/C][C]0.018293[/C][C]0.945122[/C][C]4e-06[/C][/ROW]
[ROW][C][155000,160000[[/C][C]157500[/C][C]1[/C][C]0.006098[/C][C]0.95122[/C][C]1e-06[/C][/ROW]
[ROW][C][160000,165000[[/C][C]162500[/C][C]2[/C][C]0.012195[/C][C]0.963415[/C][C]2e-06[/C][/ROW]
[ROW][C][165000,170000[[/C][C]167500[/C][C]0[/C][C]0[/C][C]0.963415[/C][C]0[/C][/ROW]
[ROW][C][170000,175000[[/C][C]172500[/C][C]1[/C][C]0.006098[/C][C]0.969512[/C][C]1e-06[/C][/ROW]
[ROW][C][175000,180000[[/C][C]177500[/C][C]2[/C][C]0.012195[/C][C]0.981707[/C][C]2e-06[/C][/ROW]
[ROW][C][180000,185000[[/C][C]182500[/C][C]0[/C][C]0[/C][C]0.981707[/C][C]0[/C][/ROW]
[ROW][C][185000,190000[[/C][C]187500[/C][C]0[/C][C]0[/C][C]0.981707[/C][C]0[/C][/ROW]
[ROW][C][190000,195000[[/C][C]192500[/C][C]0[/C][C]0[/C][C]0.981707[/C][C]0[/C][/ROW]
[ROW][C][195000,2e+05[[/C][C]197500[/C][C]1[/C][C]0.006098[/C][C]0.987805[/C][C]1e-06[/C][/ROW]
[ROW][C][2e+05,205000[[/C][C]202500[/C][C]0[/C][C]0[/C][C]0.987805[/C][C]0[/C][/ROW]
[ROW][C][205000,210000[[/C][C]207500[/C][C]0[/C][C]0[/C][C]0.987805[/C][C]0[/C][/ROW]
[ROW][C][210000,215000[[/C][C]212500[/C][C]0[/C][C]0[/C][C]0.987805[/C][C]0[/C][/ROW]
[ROW][C][215000,220000[[/C][C]217500[/C][C]0[/C][C]0[/C][C]0.987805[/C][C]0[/C][/ROW]
[ROW][C][220000,225000[[/C][C]222500[/C][C]0[/C][C]0[/C][C]0.987805[/C][C]0[/C][/ROW]
[ROW][C][225000,230000[[/C][C]227500[/C][C]0[/C][C]0[/C][C]0.987805[/C][C]0[/C][/ROW]
[ROW][C][230000,235000[[/C][C]232500[/C][C]1[/C][C]0.006098[/C][C]0.993902[/C][C]1e-06[/C][/ROW]
[ROW][C][235000,240000][/C][C]237500[/C][C]1[/C][C]0.006098[/C][C]1[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153454&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153454&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[0,5000[	2500	12	0.073171	0.073171	1.5e-05
[5000,10000[	7500	4	0.02439	0.097561	5e-06
[10000,15000[	12500	1	0.006098	0.103659	1e-06
[15000,20000[	17500	1	0.006098	0.109756	1e-06
[20000,25000[	22500	2	0.012195	0.121951	2e-06
[25000,30000[	27500	1	0.006098	0.128049	1e-06
[30000,35000[	32500	4	0.02439	0.152439	5e-06
[35000,40000[	37500	3	0.018293	0.170732	4e-06
[40000,45000[	42500	4	0.02439	0.195122	5e-06
[45000,50000[	47500	3	0.018293	0.213415	4e-06
[50000,55000[	52500	1	0.006098	0.219512	1e-06
[55000,60000[	57500	6	0.036585	0.256098	7e-06
[60000,65000[	62500	8	0.04878	0.304878	1e-05
[65000,70000[	67500	5	0.030488	0.335366	6e-06
[70000,75000[	72500	5	0.030488	0.365854	6e-06
[75000,80000[	77500	8	0.04878	0.414634	1e-05
[80000,85000[	82500	6	0.036585	0.45122	7e-06
[85000,90000[	87500	5	0.030488	0.481707	6e-06
[90000,95000[	92500	11	0.067073	0.54878	1.3e-05
[95000,1e+05[	97500	11	0.067073	0.615854	1.3e-05
[1e+05,105000[	102500	5	0.030488	0.646341	6e-06
[105000,110000[	107500	12	0.073171	0.719512	1.5e-05
[110000,115000[	112500	7	0.042683	0.762195	9e-06
[115000,120000[	117500	3	0.018293	0.780488	4e-06
[120000,125000[	122500	3	0.018293	0.79878	4e-06
[125000,130000[	127500	4	0.02439	0.823171	5e-06
[130000,135000[	132500	3	0.018293	0.841463	4e-06
[135000,140000[	137500	8	0.04878	0.890244	1e-05
[140000,145000[	142500	5	0.030488	0.920732	6e-06
[145000,150000[	147500	1	0.006098	0.926829	1e-06
[150000,155000[	152500	3	0.018293	0.945122	4e-06
[155000,160000[	157500	1	0.006098	0.95122	1e-06
[160000,165000[	162500	2	0.012195	0.963415	2e-06
[165000,170000[	167500	0	0	0.963415	0
[170000,175000[	172500	1	0.006098	0.969512	1e-06
[175000,180000[	177500	2	0.012195	0.981707	2e-06
[180000,185000[	182500	0	0	0.981707	0
[185000,190000[	187500	0	0	0.981707	0
[190000,195000[	192500	0	0	0.981707	0
[195000,2e+05[	197500	1	0.006098	0.987805	1e-06
[2e+05,205000[	202500	0	0	0.987805	0
[205000,210000[	207500	0	0	0.987805	0
[210000,215000[	212500	0	0	0.987805	0
[215000,220000[	217500	0	0	0.987805	0
[220000,225000[	222500	0	0	0.987805	0
[225000,230000[	227500	0	0	0.987805	0
[230000,235000[	232500	1	0.006098	0.993902	1e-06
[235000,240000]	237500	1	0.006098	1	1e-06

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 50 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

Parameters (R input):

par1 = 50 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
if (par3 == 'TRUE') par3 <- TRUE
if (par3 == 'FALSE') par3 <- FALSE
if (par4 == 'Unknown') par1 <- as.numeric(par1)
if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1)
if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5)
if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5)
if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5)
if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5)
if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5)
if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5)
if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5)
if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5)
bitmap(file='test1.png')
if(is.numeric(x[1])) {
if (is.na(par1)) {
myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3)
} else {
if (par1 < 0) par1 <- 3
if (par1 > 50) par1 <- 50
myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3)
}
} else {
plot(mytab <- table(x),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency')
}
dev.off()
if(is.numeric(x[1])) {
myhist
n <- length(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('histogram.htm','Frequency Table (Histogram)',''),6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bins',header=TRUE)
a<-table.element(a,'Midpoint',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE)
a<-table.element(a,'Density',header=TRUE)
a<-table.row.end(a)
crf <- 0
if (par3 == FALSE) mybracket <- '[' else mybracket <- ']'
mynumrows <- (length(myhist$breaks)-1)
for (i in 1:mynumrows) {
a<-table.row.start(a)
if (i == 1)
dum <- paste('[',myhist$breaks[i],sep='')
else
dum <- paste(mybracket,myhist$breaks[i],sep='')
dum <- paste(dum,myhist$breaks[i+1],sep=',')
if (i==mynumrows)
dum <- paste(dum,']',sep='')
else
dum <- paste(dum,mybracket,sep='')
a<-table.element(a,dum,header=TRUE)
a<-table.element(a,myhist$mids[i])
a<-table.element(a,myhist$counts[i])
rf <- myhist$counts[i]/n
crf <- crf + rf
a<-table.element(a,round(rf,6))
a<-table.element(a,round(crf,6))
a<-table.element(a,round(myhist$density[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
} else {
mytab
reltab <- mytab / sum(mytab)
n <- length(mytab)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Category',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,labels(mytab)$x[i],header=TRUE)
a<-table.element(a,mytab[i])
a<-table.element(a,round(reltab[i],4))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code